Biology subjects

Mohammad, M.

Publications and source records attributed to Mohammad, M..

4 recordsLinked to original sources

bioRxiv2024

The metabolic benefits of thermogenic stimulation are preserved in aging

Adipose thermogenesis has been actively investigated as a therapeutic target for improving metabolic dysfunction in obesity. However, its applicability to middle-aged and older populations, which bear the highest obesity prevalence in the US (approximately 40%), remains uncertain due to age-related decline in thermogenic responses. In this study, we investigated the effects of chronic thermogenic stimulation using the {beta}3-adrenergic (AR) agonist CL316,243 (CL) on systemic metabolism and adipose function in aged (18-month-old) C57BL/6JN mice. Sustained {beta}3-AR treatment resulted in reduced fat mass, increased energy expenditure, increased fatty acid oxidation and mitochondrial activity in adipose depots, improved glucose homeostasis, and a favorable adipokine profile. At the cellular level, CL treatment increased uncoupling protein 1 (UCP1)-dependent thermogenesis in brown adipose tissue (BAT). However, in white adipose tissue (WAT) depots, CL treatment increased glycerol and lipid de novo lipogenesis (DNL) and turnover suggesting the activation of the futile substrate cycle of lipolysis and reesterification in a UCP1-independent manner. Increased lipid turnover was also associated with the simultaneous upregulation of proteins involved in glycerol metabolism, fatty acid oxidation, and reesterification in WAT. Further, a dose-dependent impact of CL treatment on inflammation was observed, particularly in subcutaneous WAT, suggesting a potential mismatch between fatty acid supply and oxidation. These findings indicate that chronic {beta}3-AR stimulation activates distinct cellular mechanisms that increase energy expenditure in BAT and WAT to improve systemic metabolism in aged mice. Our study provides foundational evidence for targeting adipose thermogenesis to improve age-related metabolic dysfunction.

pharmacology and toxicology↗

bioRxiv2022

Using Attention-based Deep Learning to Predict ERG:TMPRSS2 Fusion Status in Prostate Cancer from Whole Slide Images

Prostate cancer (PCa) is associated with several genetic alterations which play an important role in the disease heterogeneity and clinical outcome including gene fusion between TMPRSS2 and members of the ETS family of transcription factors specially ERG. The expanding wealth of pathology whole slide images (WSIs) and the increasing adoption of deep learning (DL) approaches offer a unique opportunity for pathologists to streamline the detection of ERG:TMPRSS2 fusion status. Here, we used two large cohorts of digitized H&E-stained slides from radical prostatectomy specimens to train and evaluate a DL system capable of detecting the ERG fusion status and also detecting tissue regions of high diagnostic and prognostic relevance. Slides from the PCa TCGA dataset were split into training (n=318), validation (n=59), and testing sets (n=59) with the training and validation sets being used for training the model and optimizing its hyperparameters, respectively while the testing set was used for evaluating the performance. Additionally, we used an internal testing cohort consisting of 314 WSIs for independent assessment of the models performance. The ERG prediction model achieved an Area Under the Receiver Operating Characteristic curve (AUC) of 0.72 and 0.73 in the TCGA testing set and the internal testing cohort, respectively. In addition to slide-level classification, we also identified highly attended patches for the cases predicted as either ERG-positive or negative which had distinct morphological features associated with ERG status. We subsequently characterized the cellular composition of these patches using HoVer-Net model trained on the PanNuke dataset to segment and classify the nuclei into five main categories. Notably, a high ratio of neoplastic cells in the highly-attended regions was significantly associated with shorter overall and progression-free survival while high ratios of immune, stromal and stromal to neoplastic cells were all associated with longer overall and metastases-free survival. Our work highlights the utility of deploying deep learning systems on digitized histopathology slides to predict key molecular alteration in cancer together with their associated morphological features which would streamline the diagnostic process.

pathology↗

bioRxiv2022

Cystatin F (Cst7) drives sex-dependent changes in microglia in an amyloid-driven model of Alzheimer's Disease

Microglial endolysosomal (dys)function is strongly implicated in neurodegeneration. Transcriptomic studies show that a microglial state characterised by a set of genes involved in endolysosomal function is induced in both mouse Alzheimers Disease (AD) models and in human AD brain and that the onset of this state is emphasized in females. Cst7 (encoding protein Cystatin F) is among the most highly upregulated genes in these microglia. However, despite such striking and robust upregulation, the sex-specific function of Cst7 in neurodegenerative disease is not understood. Here, we crossed Cst7-/- mice with the AppNL-G-F mouse to test the role of Cst7 in a model of amyloid-driven AD. Surprisingly, we found that Cst7 plays a sexually dimorphic role regulating microglia in this model. In females, Cst7-deficient microglia had greater endolysosomal gene expression, lysosomal burden, and amyloid beta (A{beta}) burden in vivo and were more phagocytic in vitro. However, in males, Cst7-deficient microglia were less inflammatory and had a reduction in lysosomal burden but had no change in A{beta} burden. This study has important implications for AD research, confirming the functional role of a gene which is commonly upregulated in disease models, but also raising crucial questions on sexual dimorphism in neurodegenerative disease and the interplay between endolysosomal and inflammatory pathways in AD pathology.

neuroscience↗

bioRxiv2021

An intrinsic endothelial dysfunction causes cerebral small vessel disease

Small Vessel Disease (SVD) is the leading cause of vascular dementia, causes a quarter of strokes, and worsens stroke outcomes(1, 2). The disease is characterised by cerebral small vessel and white matter pathology, but the underlying mechanisms are poorly understood. Classically, the microvascular and tissue damage has been considered secondary to extrinsic factors, such as hypertension, consisting of microvessel stiffening, impaired vasoreactivity and blood-brain barrier dysfunction identified in human sporadic SVDs. However, increasing evidence points to an underlying vulnerability to SVD-related brain damage, not just extrinsic factors. Here, in a novel normotensive transgenic rat model where the phospholipase flippase Atp11b is deleted, we show pathological, imaging and behavioural changes typical of those in human sporadic SVD, but that occur without hypertension. These changes are due to an intrinsic endothelial cell dysfunction, identified in vessels of the brain white matter and the retina, with pathological evidence of vasoreactivity and blood-brain barrier deficits, which precipitate a secondary maturation block in oligodendroglia and myelin disruption around the small vessels. This highlights that an intrinsic endothelial dysfunction may underlie vulnerability to human sporadic SVD, providing alternative therapeutic targets to prevent a major cause of stroke and dementia.

neuroscience↗